The evolution of software broadly classified into the era of the lack of computer and after the introduction of computers. Before the computer era is divided into primitive and mechanical era. Whereas in the era after the introduction of computers, software evolution follows the evolution of the computer hardware itself.
The era before the introduction of computer software are classified into two eras, namely:
1. Primitive era (± 300 BC) on which the software is made by performing simple instructions by using code similar motion semaphore.
2. Mechanical Era (1840-1930’s) that apply to the use of equipment and machinery Analytical Engine punch cards.
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Unquestionable computer have been use and dig in many different aspect of human life. Lets have a look glance history of computer till we known right now.
Of course the world itself have changed, and its also causing different development of technology. And as we all know technology these days are more familiar with computer as its basic power and brain. At the first development computer was use as scientific investigation, but lately its used as military advanced technology during world war II.
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The growth of viruses especially today are consider more worms as their spread infecting traffic and became big in volume. As we know there are several types of worms, most of them infecting computer or specific file with the help of internet. Internet in here of course trigger by something, commonly from email or by downloading certain files.
Based on the history as well some traffic infection by worms already occurs long time ago, As examples, Christma Exec and Morris worms are quite popular back then. Lets have a look more further about it.
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Just as the way the worm network finds its next victim is important for its speed and its long-term survivability and penetration, the way in which the worm is introduced is another concern. A common scenario to imagine is a malicious attacker introducing a worm in a public computer lab one evening. By carefully considering the point and variety of introduction mechanisms, Internet worms can achieve different goals.
Single point
The classic paradigm of the introduction of a worm is to use a single point of origin, such as a single Internet system. This host is set up to launch the worm and infect a number of child nodes, carrying the worm with it. These new nodes then begin the next round of target identification and compromise.
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Another targeting and direction method that can be used by a worm is that of directing its attack at a particular network. In this scenario, a worm carries a target network it is to penetrate and focuses its efforts on that network. This type of worm attack would be used in information warfare.
This type of attack can be achieved in two major ways. In the first, the worm network is introduced and immediately begins its assault on the target network. In doing this, the worm can maximize its assault before the target network’s defenses are raised. However, the relatively small number of sources can make it easy to filter based on the source location.
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Island hopping named because it treats network blocks as islands on which it focuses attention before hopping away to a new, random destination. First discussed as a theoretical spread model after the release of Code Red 1, this spread pattern has proven to be highly effective in the long term.
The amount of attention spent on each network block can vary depending on the worm implementation. Typically, these boundaries fall on classfull network boundaries, such as /24, /16, /8, and, of course, /0. While this does not match many of today’s classless networks (which are subnetted on nonoctet boundaries), it does work well for the average case.
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The growth of worms development are quite enormous and its need to be look after as precaution on saving your personal data. For that lets see its traffic patterns as below:
1. Predicted traffic patterns
Because they resemble living systems in some fashion, it is possible to model the growth and reproduction of network worms. Their growth patterns are governed by the rate of infection and the number of vulnerable hosts at any given point. Similarly, their traffic patterns, in their scans and attacks, are determined by the number of active worms at any time and the amount of traffic per node.
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